Ubiquitous Computing Systems

Research Staff

  • Prof. Keiichi Yasumoto

    Prof.
    Keiichi Yasumoto

  • Prof. Yutaka Aralawa

    Assoc.Prof.
    Yutaka Arakawa

  • Assist.Prof. Hirohiko Suwa

    Assist.Prof.
    Hirohiko Suwa

  • Assist.Prof. Manato Fujimoto

    Assist.Prof.
    Manato Fujimoto

  • Assist.Prof. Teruhiro Mizumoto

    Assist.Prof.
    Teruhiro Mizumoto

E-mail { yasumoto, ara, h-suwa, manato, teruhiro-m }[at] is.naist.jp

Research Area

Ubiquitous computing systems utilize a lot of sensors and embedded/mobile devices in a harmonious manner and efficiently provide users with sophisticated services by recognizing real world contexts. Our lab conducts data collection, data analysis, and application development for solving the various challenging issues of real world. The main themes are as follows:

Smart home

Recognizing and predicting daily living activities in smart homes using sensor devices

Elderly monitoring systems using BLE devices

Smart appliance control

Smart life

Sport sensing and coaching with accelerometers and myo sensors

Walking pace control through music tempo control

Estimating physiological and mental states using various sensors

Estimating QoL with wearable sensors

Smart city

Participatory sensing systems

Behavior change for smart community

Video curation for smart tourism

Edge/fog computing based IoT platform

Key Features

We are conducting research using a smart home facility built within the university. This facility provides an actual home environment where various home appliances are deployed as in an ordinary household. In addition, this facility is equipped with special sensors including a high-accuracy indoor positioning system, wireless power meters, door sensors, and others. We are collecting data while subjects are actually living in this facility and develop various methods including activity recognition and automatic appliance control using the collected sensor data. We are also conducting research on smart life and smart cities through development of platforms for participatory sensing and IoT data processing as well as smart IoT devices including tiny all-in-one sensor boards and smart appliances.
Each student selects research topics according to his/her own interests through several brainstorming meetings with advisers. Advisers provide students with kind and careful direction to advance their research as well as suggestions to improve their programming, writing, and presentation skills. Students receive various opportunities to present their research results at domestic/international workshops and conferences.

Fig.1 Home appliance control system through social network services

Fig.1 Smart Home

Fig.2 Support system for emergency rescue operations

Fig.2 Smart Life

Fig.3 Participatory sensing by mobile users

Fig.3 Smart-city